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    <p>MongoDB has <a href="http://www.mongodb.org/display/DOCS/Geospatial+Indexing" rel="nofollow">support for spatial indexes built-in</a>, so all you'd need to do is load your points using the correct format, create the spatial index, and then run your queries.</p> <p>For a quick example, I loaded the center points for all 50 states in the mongo shell:</p> <pre><code>&gt; db.places.ensureIndex({loc: "2d"}) &gt; db.places.save({name: "AK", loc: {long: -152.2683, lat: 61.3850}}) &gt; db.places.save({name: "AL", loc: {long: -86.8073, lat: 32.7990}}) &gt; db.places.save({name: "AR", loc: {long: -92.3809, lat: 34.9513}}) &gt; db.places.save({name: "AS", loc: {long: -170.7197, lat: 14.2417}}) &gt; ... </code></pre> <p>Next, to query for the <strong>6 nearest points to a given location</strong>:</p> <pre><code>&gt; db.places.find({loc: { $near: {long: -90, lat: 50}}}).limit(6) {"name" : "WI", "loc" : { "long" : -89.6385, "lat" : 44.2563 } } {"name" : "MN", "loc" : { "long" : -93.9196, "lat" : 45.7326 } } {"name" : "MI", "loc" : { "long" : -84.5603, "lat" : 43.3504 } } {"name" : "IA", "loc" : { "long" : -93.214, "lat" : 42.0046 } } {"name" : "IL", "loc" : { "long" : -89.0022, "lat" : 40.3363 } } {"name" : "ND", "loc" : { "long" : -99.793, "lat" : 47.5362 } } </code></pre> <p>Next, to query for <strong>all points within 10km of a given location</strong>. Since I'm calculating the nearest states, I'll use 888km (which is approximately 8 degrees of latitude):</p> <pre><code>&gt; db.places.find({loc: { $near: {long: -90, lat: 50}, $maxDistance: 8}}) {"name" : "WI", "loc" : { "long" : -89.6385, "lat" : 44.2563 } } {"name" : "MN", "loc" : { "long" : -93.9196, "lat" : 45.7326 } } </code></pre> <p>Since <a href="http://en.wikipedia.org/wiki/Latitude#Degree_length" rel="nofollow">one degree of latitude is <strong>approximately</strong> 111.12km</a>, you'd use a <code>$maxDistance: 0.08999</code> to represent 10km for your application.</p> <p><strong>Updated</strong> By default MongoDB assumes an "idealized flat earth model" but this results in inaccuracies since longitude lines converge at the poles. <a href="http://www.mongodb.org/display/DOCS/Geospatial+Indexing" rel="nofollow">MongoDB versions 1.7+ support spherical distance calculations</a>, which provides the increased precision.</p> <p>Here is an example of running the above query using spherical distance. the <code>maxDistance</code> is in radians, so we need to divide by the earth's average radius:</p> <pre><code>&gt; db.runCommand({geoNear: "places", near: [-90, 50], spherical: true, maxDistance: 800/6378}); (summarizing results as they're too verbose to include) "MN" dis: 0.087.. "WI" dis: 0.100.. "ND" dis: 0.120.. </code></pre>
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    1. CO+1. Much easier to use a database with spatial extensions. There are [spatial extensions in MySQL](http://dev.mysql.com/doc/refman/5.6/en/spatial-extensions.html) too, see also [here](http://stackoverflow.com/questions/1006654/fastest-distance-lookup-given-latitude-longitude).
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    2. COWhat is the unit of `$maxDistance`?? There is a big whiffy spherical geometry smell about this answer ... it seems to be taking no account of the fact that a degree of **longitude** is about 111 km at the equator reducing to **ZERO** km at the poles.
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    3. COMy example was simply to demonstrate that the Mongo spatial extensions exist. The link I provided shows how to use either the flat or spherical distance capabilities (depending on which version of the software being used).
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